// school · ai-safety-governance
🛡️AI Safety & Governance
Compliance, explainability, bias detection, red-teaming, and responsible AI. Non-negotiable for regulated industries.
Start This School// career outcomes
Where This School Takes You
// core skills
What You Will Master
// your path
Path Through This School
Phase 01
Foundation
Prove your fundamentals. Python, Git, SQL, APIs, Docker, and AI basics — calibrated to your level before you touch AI Safety & Governance.
Phase 02
Build
Work through real AI Safety & Governance tickets inside virtual companies. Ship features, fix bugs, and build systems under production constraints.
Phase 03
Prove
Every submission is scored across 5 dimensions. Build a verified Proof-of-Competency profile that proves you can do the work of a AI Safety Engineer.
// your faculty
Your Faculty
Dr. Adaeze Nwosu
Dean
Deeply principled. Sees AI safety not as a constraint but as the foundation of trustworthy systems. Inspires responsibility.
James
Lead Instructor
Meticulous about compliance. Teaches through real-world consequences. Makes regulatory constraints feel like engineering challenges, not bureaucratic overhead.
Lucia
SHAP, LIME, model interpretability
Omar
Adversarial testing, bias detection, alignment
Ready to start AI Safety & Governance?
Begin with Foundation. Prove your baseline. Then build real systems.
Start Building